当前位置: X-MOL 学术Mech. Mach. Theory › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A novel framework for high-speed cam curve synthesis: piecewise high-order interpolation, pointwise scaling and piecewise modulation
Mechanism and Machine Theory ( IF 5.2 ) Pub Date : 2021-08-16 , DOI: 10.1016/j.mechmachtheory.2021.104477
Hong Luo 1, 2 , Jianwu Yu 2 , Lijun Li 1 , Kaifeng Huang 2 , Yuming Zhang 1 , Kai Liao 1
Affiliation  

This study proposes a novel mathematical framework for optimal synthesis of high-speed cam curves, comprising three key aspects: piecewise high-order interpolation (PHOI), pointwise scaling and piecewise modulation. In this framework, PHOI is responsible for constructing a smooth and faithful cam curve under multiorder motion constraints (including displacement, velocity, acceleration and jerk), and pointwise scaling and piecewise modulation are further introduced for optimal tuning of nodal and internodal motion parameters. Mathematically, the combination of PHOI, pointwise scaling and/or piecewise modulation will enable a full and direct control of local/global motion parameters for enhanced high-speed performance of the synthesized cam curve. Concerning the validation of this framework, three detailed numerical examples (curve reconstruction, kinematic and dynamic optimizations) are performed. The excellent interpolation accuracy of PHOI, improved motion continuity by pointwise scaling, lowered motion peaks by pointwise scaling and piecewise modulation, and reduced dynamic error of the optimized cam curve collectively demonstrate the effectiveness and versatility of the proposed framework in data-driven reconstruction and application-oriented optimization of high-speed precision cam profiles.



中文翻译:

一种高速凸轮曲线合成的新框架:分段高阶插值、逐点缩放和分段调制

本研究提出了一种用于高速凸轮曲线优化合成的新型数学框架,包括三个关键方面:分段高阶插值 (PHOI)、逐点缩放和分段调制。在此框架中,PHOI 负责在多阶运动约束(包括位移、速度、加速度和加加速度)下构建平滑且忠实的凸轮曲线,并进一步引入逐点缩放和分段调制以优化节点和节点间运动参数。在数学上,PHOI、逐点缩放和/或分段调制的组合将实现对局部/全局运动参数的全面和直接控制,以增强合成凸轮曲线的高速性能。关于这个框架的验证,三个详细的数值例子(曲线重建,运动学和动态优化)。PHOI 出色的插值精度、通过逐点缩放提高运动连续性、通过逐点缩放和分段调制降低运动峰值以及降低优化凸轮曲线的动态误差共同证明了所提出的框架在数据驱动重建和应用中的有效性和通用性面向高速精密凸轮轮廓的优化。

更新日期:2021-08-17
down
wechat
bug